In general, previous audio captioning models use an encoder-decoder architecture to handle the sequence-to-sequence nature of the problem. An early attempt, which is based on the encoder-decoder model with an attention mechanism, is proposed in [1]}. A different encoder-decoder model is presented with gated recurrent units (GRU) using a new Chinese audio captioning dataset [2]}. To solve infrequent classes problems in the captions, an encoder-decoder model with caption decoder and content word decoder is presented in [3]}. Pre-trained audio and text embeddings increase the performance of audio captioning in the studies [4]}, [5]}.
